Conference Proceedings

Workload-aware reviewer recommendation using a multi-objective search-based approach

WHA Al-Zubaidi, P Thongtanunam, HK Dam, C Tantithamthavorn, A Ghose

Proceedings of the 16th ACM International Conference on Predictive Models and Data Analytics in Software Engineering | ACM | Published : 2020

Abstract

Reviewer recommendation approaches have been proposed to provide automated support in finding suitable reviewers to review a given patch. However, they mainly focused on reviewer experience, and did not take into account the review workload, which is another important factor for a reviewer to decide if they will accept a review invitation. We set out to empirically investigate the feasibility of automatically recommending reviewers while considering the review workload amongst other factors. We develop a novel approach that leverages a multi-objective meta-heuristic algorithm to search for reviewers guided by two objectives, i.e., (1) maximizing the chance of participating in a review, and (..

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